Soumya Kanti Sarkar

 AN EMPIRICAL STUDY ON THE INFLUENCE OF GENDER IDENTITY ON APPAREL CONSUMPTION By Sudipta Roy A Dissertation Submitted to the faculty of Globsyn Business School in Partial Fulfillments of the Requirements for the Post Graduate Diploma in Management April, 2017 DEDICATION I would like to dedicate this dissertation to my parents, all the faculty members of Globsyn Business School and all my classmates who have made these two years a memorable journey for me. AN EMPIRICAL STUDY ON THE INFLUENCE OF GENDER IDENTITY ON APPAREL CONSUMPTION By Sudipta Roy Approved: Dr. Debraj Datta Internal Guide Associate Professor – Marketing Globsyn Business School CERTIFICATE FROM INTERNAL GUIDE Date: The Dean Globsyn Business School Kolkata West Bengal India Dear Sir, Sub: candidate for Post Graduate Management Course I have the pleasure of forwarding the following project dissertation. 1. Name of the Candidate: SUDIPTA ROY 2. Title of Study: An empirical study on the influence of gender identity on apparel consumption 3. Date of Submission: 4. Specialization Field: Marketing 5. Pages in Study: 26 I further certify the following: 1. The candidate has completed the work to my satisfaction. 2. This is an original work of the candidate and to the best of my knowledge has not been published anywhere else. 3. The use of existing works has been duly acknowledged. 4. The candidate has spent a minimum of 30 hours while conducting the study. The dissertation may now be evaluated for the purpose of awarding Postgraduate Diploma. Yours Sincerely, Internal Guide Name of the Guide: Dr. Debraj Datta DECLARATION OF ORIGINALITY This is to declare that the work is entirely my own and not of any other person, unless explicitly acknowledged (including citation of published and unpublished sources). The work has not previously been submitted in any form to Globsyn Business School, or to any other institution for assessment for any other purpose. I further declare that I have devoted a minimum of 30 hours to study this topic. Name: Sudipta Roy Enrolment Number:- Signed: Date: ACKNOWLEDGEMENTS The author wishes to express her gratitude and deepest regards to her internal guide (Dr. Debraj Datta) for his exemplary guidance, monitoring and constant encouragement throughout the course of this dissertation. The author would also like to express her deep sense of gratitude to Globsyn Business School and the Registrar’s Office for giving this opportunity. The author is obliged to all her respondents for their valuable time and co-operation they showed to complete this survey. Lastly, the author wishes to thank the god, her parents and friends for their constant encouragement and support without which the dissertation would not have been possible. TABLE OF CONTENTS 1. Approval Note 2. Certificate from Internal Guide 3. Declaration of Originality 4. Acknowledgement 5. Table of Content 6. Abstract 7. Dissertation: Chapter 1 8. Dissertation: Chapter 2 9. Dissertation: Chapter 3 10. Dissertation: Chapter 4 11. Dissertation: Chapter 5 12. Webliography ABSTRACT Title of Study: AN EMPIRICAL STUDY ON THE INFLUENCE OF GENDER IDENTITY ON APPAREL CONSUMPTION Objective: The main objective of this study was to study the impact of age, pricing, offers and discounts on apparel consumption by different gender. The chosen topic has been investigated from the point of view of the consumer, so as to gain an understanding of their individual perspectives on the issue. Research Methodology: A primary research has been done by collecting data from 48 respondents aged between 15-30 and above years, both male and female with a questionnaire. Theory: The theoretical concept which has been addressed here is consumer acceptance or behavior. The aim was on one hand to offer a comprehensive view of the concept while also to study consumers’ attitudes towards carbonated soft drink brands in India. Research Limitations: The two most important limitations of this research are method and number. For this research study the method was the most appropriate and the number of consumer views assessed was acceptable. CHAPTER 1 1. INTRODUCTION 1.1 Study Background The ever-evolving fashion industry is a clear reflection of the changing patterns in the social, political, technological and economic environment of a society. The past few decades have seen significant and diverse changes in consumer habits and lifestyles. At long last, garment purchase has come of age, with both male and female consumers becoming increasingly brand and fashion conscious. With the emergence of a contemporary social structure, garment purchase is no longer the forte of women alone. Research, national and international, expounds on the purchase decisions of the New Man who is becoming more fashion conscious and trend savvy when it comes to apparel. This study is an attempt to identify certain gender-based antecedents of garment purchase involvement. An attempt has also been made to identify the key drivers that influence the decision making process for garment purchase, separately for male and female customers. The findings demonstrate a paradigm shift in attitudes and purchase patterns, which can have important implications for the marketer. 1.2 Objectives: The study is concerned with the following objectives: To study the effect of pricing, offers and discounts on apparel buying behavior of different genders To study the effect of advertisements on apparel buying behavior of different age categories of gender To study the impact of demography viz. age, gender and income and the influence of reference groups viz. friends and family on apparel buying behavior of different genders 1.3 Statement of the problem: The study was conducted to know the brand preference and factors influencing young consumers of apparels. Cloth shopping is an important product item in the modern society. It is mainly concentrated on the consumption among youth of different gender. It is found that a great important for the study. The study examines key attitude of buying and brand perception with preference that are considered as important cues, which lead youth to select particular brand of apparel. 1.4 Scope of the study: Looking at the current trend of fashion style expansion in India, it is the tier-II cities where the real action is going to take place in the near future. There is a huge scope for further study, concentrating on the tastes and buying behaviors of different gender. Also it would be interesting to track the positive and negative impacts and the change in the buying pattern of Indian consumers on apparel buying behavior. 1.5 Research methodology: A study can be initiated with a proper design and methodology to bring out the suitable findings which are reliable and applicable to solve the problems and useful to carry out further research of interest. It needs a careful analysis of the consumer through which the results for the present study can be crystallized for framing suitable solutions. In this chapter, a brief description of the research methodology adopted in selection of the area, sampling of customers, method of data collection and the tools used for data analysis are presented. 1.5.1 Data collection Primary data collection technique was adopted using a self-administered online questionnaire. The questionnaire was prepared and distributed using the website – https://www.google.com/forms/about/. Data was collected though web-links, e-mails and social networking sites. The respondents were given a brief introduction about the purpose and importance of the study. Enough time was given to them to think over the answers for the questions to have reliability of response. Utmost effort is employed to ensure removal of biases in the questionnaire 1.5.2 Tools of Analysis 1. Questionnaire 2. Percentage Analysis 1.5.3 Analytical Tools 1. Graphs 2. Tables 3. Diagrams 1.5.4 Limitations of study 1. Very limited time available for this study 3. Many of the questionnaires had irrelevant and incorrect answers filled in by the respondents leading to errors in the study 4. Sample size is comparatively small for a study of vast relevance 5. Lack of experience CHAPTER 2 2. LITERATURE REVIEW Consumer researchers have been examining the impact of gender identity—the degree to which an individual identifies with masculine and feminine personality traits—on various consumer variables for nearly four decades. However, significant gender identity findings in consumer research have been rare, perhaps because of (1) operationalization problems (Palan, Kiecker, and Areni 1999), (2) inappropriate interpretation and application of gender identity to consumer variables (Gould 1996), or (3) blurring gender categories (Firat 1993). Pettinger (2005) said that the gender embedded in the fashion industry where the majority of customer service is feminized. The products itself are inherently gender. Clothes represent gender, class and status. This makes up the gender consumption environment in both shopper, physical spaces of shop and consumer. Front-lines staffs-customer-services inevitably are influenced by gender in manipulating and displaying the products. The study of Nixon (1996) stated that the store design during 1980s was used to signal masculine identity in the mass- market. Pettinger (2005) further claimed how the shop was gender by explaining the main components of fashion industry-gender consumption, market place, the products, bodies and sales assistant. CHAPTER 3 3. THEORY 3.1 Apparel Industry in India India is among the most attractive investment propositions for the global retailers. The retail sector in India accounts for nearly 22 per cent of the country's gross domestic product (GDP) and contributes to almost 8 per cent of the total employment. The domestic apparel market is US$ 50 billion as of 2013 and is expected to grow at a compound average growth rate (CAGR) of 13 per cent over the next seven years.  Currently, apparel industry contributes 15 per cent to the industrial production, 4 per cent to the GDP, and 17 per cent to the country's export earnings. Over 30 million people are directly employed in the apparel industry. The recent exclusion of excise duty on branded apparel has provided an incentive to retailers in terms of the overall market sentiment.  With a market size of US$ 20 billion in 2013 and accounting for 40 per cent of the overall market, men's wear is the largest segment in the Indian apparel market. In comparison, women's wear makes 35 per cent, while the kid's wear comprises only 25 per cent of the market. However by 2020, women's wear would be contributing more than men's wear. In terms of usage, casual wear leads the purchases, accounting for almost half of the total apparel sales.  The key players in the Indian market -- Madura Garments, Raymond and Arvind -- are facing increasing competition from entry of international brands. Online sales are at a nascent stage, however growing at a rapid pace. 3.2 Gender and Shopping Shopping is considered as female activity. To keep a sense of masculinity, some men avoid go shopping. Women perceives shopping as leisure, relax and enjoyable. The difference view of shopping between women and men construct the different shopping behaviors. Men’s shopping is driven by the need. Women’s shopping is motivated by reasons of enjoyment and relaxation. There is clear preference between women and men in shopping, Women like going shopping for fashions cosmetics, clothes and accessories, while men like going shopping for electronic and high-tech devices. Thus, women spend more time than men in shopping. However, men tend to spend more money in shopping than women in the context of comparable activities, (Bakewell & Mitchell 2004). CHAPTER 4 4. DATA ANALYSIS AND REPRESENTATION 4.1 Chi-Square Test of Independence between age and frequency of consumption Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent age * freq 48 100.0% 0 0.0% 48 100.0% age * freq Crosstabulation Count freq Total Randomly Once a month Once every 3 months Once a year age- - Total- Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 5.492a 3 .139 Likelihood Ratio 7.240 3 .065 Linear-by-Linear Association 1.197 1 .274 N of Valid Cases 48 a. 5 cells (62.5%) have expected count less than 5. The minimum expected count is .33. Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .338 .139 Cramer's V .338 .139 Contingency Coefficient .320 .139 N of Valid Cases 48 a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. H0: "Age is not associated with Frequency of consumption" H1: “Age is associated with Frequency of consumption " Since the p-value is greater than our chosen significance level (α = 0.05), we do not reject the null hypothesis. Rather, we conclude that there is not enough evidence to suggest an association between age and frequency of consumption. 4.2 Chi-Square Test of Independence between Sex and Frequency of consumption Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent sex * freq 48 100.0% 0 0.0% 48 100.0% sex * freq Crosstabulation Count freq Total Randomly Once a month Once every 3 months Once a year sex Female- Male 7 7 8 2 24 Total- Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 2.882a 3 .410 Likelihood Ratio 3.658 3 .301 Linear-by-Linear Association 1.303 1 .254 N of Valid Cases 48 a. 2 cells (25.0%) have expected count less than 5. The minimum expected count is 1.00. Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .245 .410 Cramer's V .245 .410 N of Valid Cases 48 a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. H0: "Sex is not associated with Frequency of consumption" H1: "Sex is associated with Frequency of consumption” Since the p-value is greater than our chosen significance level (α = 0.05), we do not reject the null hypothesis. Rather, we conclude that there is not enough evidence to suggest an association between sex and frequency of consumption. 4.3 Chi-Square Test of Independence between Sex and Amount spend by consumers for consumption Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent sex * amount 48 100.0% 0 0.0% 48 100.0% sex * amount Crosstabulation Count amount Total Between Rs 1000- Rs 2000 Rs 500- Rs 1000 More than 5000 Less than 500 sex Female- Male 8 9 6 1 24 Total- Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 9.600a 3 .022 Likelihood Ratio 11.980 3 .007 Linear-by-Linear Association 3.615 1 .057 N of Valid Cases 48 a. 4 cells (50.0%) have expected count less than 5. The minimum expected count is 1.50. Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .447 .022 Cramer's V .447 .022 N of Valid Cases 48 a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. H0: "Sex is not associated with Amount spend by consumers for consumption" H1: "Sex is associated with Amount spend by consumers for consumption” Since the p-value is less than our chosen significance level α = 0.05, we can reject the null hypothesis, and conclude that there is an association between sex and Amount spend by consumers for consumption. 4.4 Chi-Square Test of Independence between Age and Amount spend by consumers for consumption Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent age * amount 48 100.0% 0 0.0% 48 100.0% age * amount Crosstabulation Count amount Total Between Rs 1000- Rs 2000 Rs 500- Rs 1000 More than 5000 Less than 500 age- - Total- Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 3.120a 3 .373 Likelihood Ratio 3.016 3 .389 Linear-by-Linear Association 2.892 1 .089 N of Valid Cases 48 a. 5 cells (62.5%) have expected count less than 5. The minimum expected count is .50. Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .255 .373 Cramer's V .255 .373 N of Valid Cases 48 a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. H0: "Age is not associated with Amount spend by consumers for consumption" H1: "Age is associated with Amount spend by consumers for consumption” Since the p-value is greater than our chosen significance level (α = 0.05), we do not reject the null hypothesis. Rather, we conclude that there is not enough evidence to suggest an association between age and amount spend by consumers for consumption. 4.5 Chi-Square Test of Independence between Sex and Impact of Discounts Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent sex * Discounts 48 100.0% 0 0.0% 48 100.0% sex * Discounts Cross tabulation Count Discounts Total All of them None of them Only some of them Most of them sex Female- Male- Total- Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 6.123a 3 .106 Likelihood Ratio 8.441 3 .038 Linear-by-Linear Association .605 1 .437 N of Valid Cases 48 a. 4 cells (50.0%) have expected count less than 5. The minimum expected count is 1.50. Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .357 .106 Cramer's V .357 .106 N of Valid Cases 48 a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. H0: "Sex is not associated with Impact of Discounts" H1: "Sex is associated with Impact of Discounts” Since the p-value is greater than our chosen significance level (α = 0.05), we do not reject the null hypothesis. Rather, we conclude that there is not enough evidence to suggest an association between sex and impact of discounts. 4.6 Chi-Square Test of Independence between Age and Impact of Discounts age * Discounts Crosstabulation Count Discounts Total All of them None of them Only some of them Most of them age- - Total- Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 2.097a 3 .552 Likelihood Ratio 2.971 3 .396 Linear-by-Linear Association 1.934 1 .164 N of Valid Cases 48 a. 5 cells (62.5%) have expected count less than 5. The minimum expected count is .50. Symmetric Measures Value Approx. Sig. Nominal by Nominal Phi .209 .552 Cramer's V .209 .552 N of Valid Cases 48 a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. H0: "Age is not associated with Impact of Discounts" H1: "Age is associated with Impact of Discounts” Since the p-value is greater than our chosen significance level (α = 0.05), we do not reject the null hypothesis. Rather, we conclude that there is not enough evidence to suggest an association between Age and impact of discounts. CHAPTER 5 5. FINDINGS, SUGGESTIONS AND CONCLUSION 5.1 Findings There is no significance between age and frequency of purchase There is no significance between sex and frequency of purchase There is a significance between sex and amount spend by consumer for consumption There is no significance between sex and impact of discounts 5.2 Conclusion It has been noted that gender is not only a biological concept as being a male or female, but beyond. Looking at gender with different dimensions, gender is not only a market segmentation variable, it is a variable that has a strong impact on the decisions. Marketers need to understand gender based tendencies in order to better satisfy the customers. Here in case for apparel consumption both male and female customer depict completely different behavior. Webliography https://www.google.co.in/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&sqi=2&ved=0ahUKEwjN2IWSr7zTAhUQS48KHQ8DAxwQFggoMAE&url=https%3A%2F%2Fwww.ibef.org%2Fexports%2Fapparel-industry-india.aspx&usg=AFQjCNEbhrQE3kfblYjSXVGF6v7k6Zx-_Q https://www.google.co.in/url?sa=t&rct=j&q=&esrc=s&source=web&cd=3&cad=rja&uact=8&sqi=2&ved=0ahUKEwjN2IWSr7zTAhUQS48KHQ8DAxwQFgguMAI&url=http%3A%2F%2Fwww.indiantradeportal.in%2Fvs.jsp%3Flang%3D1%26id%3D0%2C30%2C50%2C163&usg=AFQjCNEjENiCj4GKuILLvKCPCACY8VBOig